QSAR Dataset

Dataset statistics

Number of variables	8
Number of observations	908
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	56.9 KiB
Average record size in memory	64.1 B

Variable types

NUM	8

Warnings

`df_index` has unique values	Unique
`SM1_Dz(z)` has 36 (4.0%) zeros	Zeros
`NdsCH` has 760 (83.7%) zeros	Zeros
`NdssC` has 622 (68.5%) zeros	Zeros

Reproduction

Analysis started	2022-08-25 09:28:47.774150
Analysis finished	2022-08-25 09:29:06.887163
Duration	19.11 seconds
Software version	pandas-profiling v2.9.0
Download configuration	config.yaml

df_index
Real number (ℝ_≥0)

UNIQUE

Distinct	908
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	454.5
Minimum	1
Maximum	908
Zeros	0
Zeros (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	1
5-th percentile	46.35
Q1	227.75
median	454.5
Q3	681.25
95-th percentile	862.65
Maximum	908
Range	907
Interquartile range (IQR)	453.5

Descriptive statistics

Standard deviation	262.2613201
Coefficient of variation (CV)	0.5770326074
Kurtosis	-1.2
Mean	454.5
Median Absolute Deviation (MAD)	227
Skewness	0
Sum	412686
Variance	68781
Monotocity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1	0.1%
625	1	0.1%
599	1	0.1%
600	1	0.1%
601	1	0.1%
602	1	0.1%
603	1	0.1%
604	1	0.1%
605	1	0.1%
606	1	0.1%
Other values (898)	898	98.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	0.1%
2	1	0.1%
3	1	0.1%
4	1	0.1%
5	1	0.1%

Value	Count	Frequency (%)
908	1	0.1%
907	1	0.1%
906	1	0.1%
905	1	0.1%
904	1	0.1%

CICO
Real number (ℝ_≥0)

Distinct	502
Distinct (%)	55.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	2.898128855
Minimum	0.667
Maximum	5.926
Zeros	0
Zeros (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0.667
5-th percentile	1.7754
Q1	2.347
median	2.934
Q3	3.407
95-th percentile	4.16925
Maximum	5.926
Range	5.259
Interquartile range (IQR)	1.06

Descriptive statistics

Standard deviation	0.7560884791
Coefficient of variation (CV)	0.2608884963
Kurtosis	-0.04150551962
Mean	2.898128855
Median Absolute Deviation (MAD)	0.5285
Skewness	0.04545787455
Sum	2631.501
Variance	0.5716697882
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2.126	14	1.5%
3.08	11	1.2%
2.377	9	1.0%
2.834	7	0.8%
2.08	7	0.8%
3.252	7	0.8%
2.508	7	0.8%
2.479	7	0.8%
3.179	6	0.7%
2.216	6	0.7%
Other values (492)	827	91.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.667	2	0.2%
0.965	3	0.3%
0.973	1	0.1%
1	3	0.3%
1.075	1	0.1%

Value	Count	Frequency (%)
5.926	1	0.1%
5.158	1	0.1%
4.88	1	0.1%
4.829	1	0.1%
4.81	1	0.1%

SM1_Dz(z)
Real number (ℝ_≥0)

ZEROS

Distinct	186
Distinct (%)	20.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.6284680617
Minimum	0
Maximum	2.171
Zeros	36
Zeros (%)	4.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0.134
Q1	0.223
median	0.57
Q3	0.89275
95-th percentile	1.4396
Maximum	2.171
Range	2.171
Interquartile range (IQR)	0.66975

Descriptive statistics

Standard deviation	0.4284590914
Coefficient of variation (CV)	0.6817515759
Kurtosis	-0.117152754
Mean	0.6284680617
Median Absolute Deviation (MAD)	0.347
Skewness	0.6950900326
Sum	570.649
Variance	0.183577193
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.223	135	14.9%
0.134	74	8.1%
0.405	69	7.6%
0.331	39	4.3%
0	36	4.0%
0.693	26	2.9%
0.56	25	2.8%
0.496	24	2.6%
0.251	21	2.3%
0.58	16	1.8%
Other values (176)	443	48.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	36	4.0%
0.134	74	8.1%
0.223	135	14.9%
0.251	21	2.3%
0.288	1	0.1%

Value	Count	Frequency (%)
2.171	1	0.1%
2.071	1	0.1%
2.044	1	0.1%
1.86	1	0.1%
1.834	1	0.1%

GATS1i
Real number (ℝ_≥0)

Distinct	557
Distinct (%)	61.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1.29359141
Minimum	0.396
Maximum	2.92
Zeros	0
Zeros (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0.396
5-th percentile	0.799
Q1	0.95075
median	1.2405
Q3	1.56225
95-th percentile	2.00985
Maximum	2.92
Range	2.524
Interquartile range (IQR)	0.6115

Descriptive statistics

Standard deviation	0.394302736
Coefficient of variation (CV)	0.3048124261
Kurtosis	0.3268399411
Mean	1.29359141
Median Absolute Deviation (MAD)	0.2995
Skewness	0.7231072608
Sum	1174.581
Variance	0.1554746476
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.941	8	0.9%
1.179	7	0.8%
0.938	7	0.8%
0.954	7	0.8%
0.871	7	0.8%
1.189	6	0.7%
1.6	6	0.7%
1.571	6	0.7%
1.077	5	0.6%
0.95	5	0.6%
Other values (547)	844	93.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.396	1	0.1%
0.421	1	0.1%
0.523	1	0.1%
0.595	1	0.1%
0.618	1	0.1%

Value	Count	Frequency (%)
2.92	1	0.1%
2.698	1	0.1%
2.672	1	0.1%
2.609	1	0.1%
2.606	1	0.1%

NdsCH
Real number (ℝ_≥0)

ZEROS

Distinct	5
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.2290748899
Minimum	0
Maximum	4
Zeros	760
Zeros (%)	83.7%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	4
Range	4
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.6053349942
Coefficient of variation (CV)	2.642520071
Kurtosis	13.81346349
Mean	0.2290748899
Median Absolute Deviation (MAD)	0
Skewness	3.400814701
Sum	208
Variance	0.3664304552
Monotocity	Not monotonic

Histogram with fixed size bins (bins=5)

Value	Count	Frequency (%)
0	760	83.7%
1	107	11.8%
2	29	3.2%
4	7	0.8%
3	5	0.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	760	83.7%
1	107	11.8%
2	29	3.2%
3	5	0.6%
4	7	0.8%

Value	Count	Frequency (%)
4	7	0.8%
3	5	0.6%
2	29	3.2%
1	107	11.8%
0	760	83.7%

NdssC
Real number (ℝ_≥0)

ZEROS

Distinct	7
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.4856828194
Minimum	0
Maximum	6
Zeros	622
Zeros (%)	68.5%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1
95-th percentile	2
Maximum	6
Range	6
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.8612789371
Coefficient of variation (CV)	1.773336224
Kurtosis	6.423355202
Mean	0.4856828194
Median Absolute Deviation (MAD)	0
Skewness	2.239090332
Sum	441
Variance	0.7418014076
Monotocity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
0	622	68.5%
1	176	19.4%
2	81	8.9%
3	18	2.0%
4	8	0.9%
6	2	0.2%
5	1	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	622	68.5%
1	176	19.4%
2	81	8.9%
3	18	2.0%
4	8	0.9%

Value	Count	Frequency (%)
6	2	0.2%
5	1	0.1%
4	8	0.9%
3	18	2.0%
2	81	8.9%

MLOGP
Real number (ℝ)

Distinct	559
Distinct (%)	61.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	2.109285242
Minimum	-2.884
Maximum	6.515
Zeros	0
Zeros (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	-2.884
5-th percentile	-0.317
Q1	1.209
median	2.127
Q3	3.105
95-th percentile	4.48745
Maximum	6.515
Range	9.399
Interquartile range (IQR)	1.896

Descriptive statistics

Standard deviation	1.433180788
Coefficient of variation (CV)	0.6794627676
Kurtosis	0.006986919075
Mean	2.109285242
Median Absolute Deviation (MAD)	0.937
Skewness	-0.03519131625
Sum	1915.231
Variance	2.054007172
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1.701	10	1.1%
0.8	10	1.1%
0.202	9	1.0%
1.064	9	1.0%
2.604	9	1.0%
1.748	9	1.0%
1.442	8	0.9%
2.193	8	0.9%
1.587	8	0.9%
1.859	7	0.8%
Other values (549)	821	90.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-2.884	1	0.1%
-2.089	1	0.1%
-2.03	1	0.1%
-1.96	1	0.1%
-1.358	1	0.1%

Value	Count	Frequency (%)
6.515	1	0.1%
6.203	1	0.1%
6.166	1	0.1%
5.934	1	0.1%
5.741	1	0.1%

LC50[-LOG(mol/L)]
Real number (ℝ_≥0)

Distinct	827
Distinct (%)	91.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	4.064430617
Minimum	0.053
Maximum	9.612
Zeros	0
Zeros (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0.053
5-th percentile	1.68385
Q1	3.15175
median	3.9875
Q3	4.9075
95-th percentile	6.48365
Maximum	9.612
Range	9.559
Interquartile range (IQR)	1.75575

Descriptive statistics

Standard deviation	1.455698446
Coefficient of variation (CV)	0.3581555655
Kurtosis	0.6638471981
Mean	4.064430617
Median Absolute Deviation (MAD)	0.867
Skewness	0.2521384377
Sum	3690.503
Variance	2.119057965
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4.208	4	0.4%
3.513	4	0.4%
3.47	3	0.3%
3.979	3	0.3%
3.926	3	0.3%
3.66	3	0.3%
4.54	2	0.2%
3.751	2	0.2%
3.841	2	0.2%
4.499	2	0.2%
Other values (817)	880	96.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.053	1	0.1%
0.15	1	0.1%
0.242	1	0.1%
0.33	1	0.1%
0.361	1	0.1%

Value	Count	Frequency (%)
9.612	1	0.1%
9.354	1	0.1%
8.916	1	0.1%
8.604	1	0.1%
8.571	1	0.1%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

First rows

	df_index	CICO	SM1_Dz(z)	GATS1i	NdsCH	NdssC	MLOGP	LC50[-LOG(mol/L)]
0	1	3.260	0.829	1.676	0	1	1.453	3.770
1	2	2.189	0.580	0.863	0	0	1.348	3.115
2	3	2.125	0.638	0.831	0	0	1.348	3.531
3	4	3.027	0.331	1.472	1	0	1.807	3.510
4	5	2.094	0.827	0.860	0	0	1.886	5.390
5	6	3.222	0.331	2.177	0	0	0.706	1.819
6	7	3.179	0.000	1.063	0	0	2.942	3.947
7	8	3.000	0.000	0.938	1	0	2.851	3.513
8	9	2.620	0.499	0.990	0	0	2.942	4.402
9	10	2.834	0.134	0.950	0	0	1.591	3.021

Last rows

	df_index	CICO	SM1_Dz(z)	GATS1i	NdsCH	NdssC	MLOGP	LC50[-LOG(mol/L)]
898	899	3.599	0.702	1.514	2	1	3.247	6.183
899	900	2.986	0.961	1.669	0	4	1.798	3.152
900	901	2.804	1.110	0.618	0	6	1.317	6.254
901	902	3.670	0.728	2.110	0	3	2.288	2.964
902	903	3.475	0.405	0.875	1	2	3.148	4.803
903	904	2.801	0.728	2.226	0	2	0.736	3.109
904	905	3.652	0.872	0.867	2	3	3.983	4.040
905	906	3.763	0.916	0.878	0	6	2.918	4.818
906	907	2.831	1.393	1.077	0	1	0.906	5.317
907	908	4.057	1.032	1.183	1	3	4.754	8.201

Overview

Variables

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Missing values

Sample

First rows

Last rows